BACKGROUND AND OBJECTIVE: The high mortality rate associated with coronary heart disease (CHD) has driven intensive research in cardiac imaging and image analysis. The advent of computed tomography angiography (CTA) has turned non-invasive diagnosis ...
Emerging evidence indicates the existence of a new class of cancer genes that act as "signal linkers" coordinating oncogenic signals between mutated and differentially expressed genes. While frequently mutated oncogenes and differentially expressed g...
Using a powerful machine learning approach, a recent study of human genomes has revealed widespread footprints of recent positive selection on standing genetic variation.
This paper discusses the problem of squatting training of stroke patients. The main idea is to correct the patient's training trajectory through an iterative learning control (ILC) method. To obtain better rehabilitation effect, a patient will typica...
Disability and rehabilitation. Assistive technology
Jul 31, 2017
PURPOSE: The potential of service robots for seniors is given increasing attention as the ageing population in Western countries will continue to grow as well as the demand for home care. In order to capture the experience of living with a robot at h...
International journal of computer assisted radiology and surgery
Jul 31, 2017
PURPOSE: Delineation of thyroid nodule boundaries from ultrasound images plays an important role in calculation of clinical indices and diagnosis of thyroid diseases. However, it is challenging for accurate and automatic segmentation of thyroid nodul...
Vast amounts of clinically relevant text-based variables lie undiscovered and unexploited in electronic medical records (EMR). To exploit this untapped resource, and thus facilitate the discovery of informative covariates from unstructured clinical n...
UNLABELLED: Intensive care unit patients are heavily monitored, and several clinically-relevant parameters are routinely extracted from high resolution signals.
OBJECTIVE: This paper builds upon work submitted as part of the 2016 PhysioNet/CinC Challenge, which used sparse coding as a feature extraction tool on audio PCG data for heart sound classification.
In this chapter, I reflect on contemporary entanglements between artificial intelligence and the neurosciences by tracing the development of Google's recent DeepMind algorithms back to their roots in neuroscientific studies of episodic memory and ima...
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